
where \(\alpha \) , and \(1-\alpha \)  are the weighting coefficientsThe non-negative weight \(\alpha \)  denotes the priorities of CUs and DUs in the resource allocation policy specified in the media access control (MAC) layer to achieve a certain notion of fairness, especially for users who suffer from poor channel conditions.indicating the impact of the different objectives. The weighted Tchebycheff method ensures to produce a set of Pareto-optimal solutions when R\(_{\text{DU,max}}\)  and R\(_{\text{CU,max}}\)  are the utopian objective points as the maximum of each objective, respectively [1]}. In the following, to solve the highly nonconvex optimization problem in () globally, we apply a global optimization approach known as the monotonic optimization method. By
exploiting monotonicity or hidden monotonicity in the objective function as well
as constraints, this method guarantees the convergence [2]}.
